首页> 外文会议>International Conference on Applications of Natural Language to Information Systems(NLDB 2005); 20050615-17; Alicante(ES) >Automatic Extraction of Semantic Relationships for WordNet by Means of Pattern Learning from Wikipedia
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Automatic Extraction of Semantic Relationships for WordNet by Means of Pattern Learning from Wikipedia

机译:通过Wikipedia的模式学习自动提取WordNet的语义关系。

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This paper describes an automatic approach to identify lexical patterns which represent semantic relationships between concepts, from an on-line encyclopedia. Next, these patterns can be applied to extend existing ontologies or semantic networks with new relations. The experiments have been performed with the Simple English Wikipedia and WordNet 1.7. A new algorithm has been devised for automatically generalising the lexical patterns found in the encyclopedia entries. We have found general patterns for the hyperonymy, hyponymy, holonymy and meronymy relations and, using them, we have extracted more than 1200 new relationships that did not appear in WordNet originally. The precision of these relationships ranges between 0.61 and 0.69, depending on the relation.
机译:本文介绍了一种自动方法,该方法可从在线百科全书中识别代表概念之间语义关系的词汇模式。接下来,可以将这些模式应用于扩展具有新关系的现有本体或语义网络。实验已使用简单英语维基百科和WordNet 1.7进行。已经设计出一种新算法,用于自动概括百科全书条目中的词汇模式。我们已经找到了关于别名,下位,整体和代名词关系的一般模式,并使用它们提取了1200多个最初未出现在WordNet中的新关系。这些关系的精度取决于关系,在0.61到0.69之间。

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